Lead Azure Data Engineer (contract)

Capgemini; Brampton; On-site; CAD 87,000 - 135,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Retirement benefits

Job summary

Capgemini is seeking a data engineering lead to design, build, and scale data pipelines using Azure Data Factory and Azure Databricks in Brampton, Canada. You will guide a 10–15 person team and collaborate with executives, product, and analytics stakeholders to deliver robust data solutions.

You will own data ingestion, transformation, and loading, ensure quality and security, and mentor the team on best practices in data engineering and DevOps.

Qualifications

• Proven leadership experience managing technical teams.
• Strong presentation, communication, and stakeholder management skills.
• Experience working in Agile and DevOps-driven environments is preferred.

Responsibilities

• Design, develop, and maintain scalable and efficient data pipeline architectures using Azure Data Factory (ADF).
• Build and manage ETL/ELT processes using Azure Databricks, with a strong understanding of Apache Spark and PySpark frameworks.
• Assemble and manage large, complex datasets that support both functional and non-functional business requirements.
• Develop and maintain data ingestion, transformation, and loading solutions using SQL and Azure Big Data technologies.
• Work closely with Executive, Product, Data, and Design teams to address data-related technical challenges and support data infrastructure needs.
• Create and maintain data tools that enable analytics and data science teams to build, optimize, and scale business solutions.
• Collaborate with data engineers, analysts, and data scientists to enhance the functionality and performance of data platforms and systems.
• Ensure data quality, reliability, security, and governance across the data ecosystem.
• Provide technical leadership and guidance to a team of 10–15 members.
• Drive project delivery, mentor team members, and support best practices in data engineering and development.
• Deliver effective presentations and communicate technical concepts clearly to both technical and business stakeholders.
• Demonstrate strong leadership, stakeholder management, and problem-solving capabilities.

Skills

Leadership

Data pipelines

Azure Data Factory

Azure Databricks

Apache Spark

PySpark

SQL

Data governance

Data quality

Security

Tools

Azure Data Factory

Azure Databricks

Apache Spark

PySpark

SQL

Job description

• Design, develop, and maintain scalable and efficient data pipeline architectures using Azure Data Factory (ADF).
• Build and manage ETL/ELT processes using Azure Databricks, with a strong understanding of Apache Spark and PySpark frameworks.
• Assemble and manage large, complex datasets that support both functional and non-functional business requirements.
• Develop and maintain data ingestion, transformation, and loading solutions using SQL and Azure Big Data technologies.
• Work closely with Executive, Product, Data, and Design teams to address data-related technical challenges and support data infrastructure needs.
• Create and maintain data tools that enable analytics and data science teams to build, optimize, and scale business solutions.
• Collaborate with data engineers, analysts, and data scientists to enhance the functionality and performance of data platforms and systems.
• Ensure data quality, reliability, security, and governance across the data ecosystem.
• Provide technical leadership and guidance to a team of 10–15 members.
• Drive project delivery, mentor team members, and support best practices in data engineering and development.
• Deliver effective presentations and communicate technical concepts clearly to both technical and business stakeholders.
• Demonstrate strong leadership, stakeholder management, and problem-solving capabilities.

Key Responsibilities

• Design, develop, and maintain scalable and efficient data pipeline architectures using Azure Data Factory (ADF).
• Build and manage ETL/ELT processes using Azure Databricks, with a strong understanding of Apache Spark and PySpark frameworks.
• Assemble and manage large, complex datasets that support both functional and non-functional business requirements.
• Develop and maintain data ingestion, transformation, and loading solutions using SQL and Azure Big Data technologies.
• Work closely with Executive, Product, Data, and Design teams to address data-related technical challenges and support data infrastructure needs.
• Create and maintain data tools that enable analytics and data science teams to build, optimize, and scale business solutions.
• Collaborate with data engineers, analysts, and data scientists to enhance the functionality and performance of data platforms and systems.
• Ensure data quality, reliability, security, and governance across the data ecosystem.
• Provide technical leadership and guidance to a team of 10–15 members.
• Drive project delivery, mentor team members, and support best practices in data engineering and development.
• Deliver effective presentations and communicate technical concepts clearly to both technical and business stakeholders.
• Demonstrate strong leadership, stakeholder management, and problem-solving capabilities.

Additional Requirements

• Proven leadership experience managing and mentoring technical teams.
• Strong presentation, communication, and stakeholder management skills.
• Experience working in Agile and DevOps-driven environments is preferred.

The pay range that the employer in good faith reasonably expects to pay for this position is $44.85/hour - $70.07/hour. Our offered benefits include medical, dental, vision and retirement benefits.

Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.